Dr. Thomas B. Smith
The research in my laboratory focuses on the ecological and evolutionary processes that generate and maintain biodiversity. In a new study involving MARC student Alex Richards, and RIMI fellow Dr. Ravinder Sehgal, we investigate the link between biodiversity and the evolution of immunity. Coevolution is thought to maintain genetic diversity in pathogen and host populations, and to contribute to the complexity of the immune system. Indeed, high levels of genetic variation have been found in the major histocompatibility complex (MHC), a highly polymorphic gene system associated with immunity in a variety of vertebrates. High levels of heterozygosity at MHC loci can be associated with higher levels of parasite and disease resistance. Empirical evidence for an association between MHC variation and pathogen prevalence is needed across a wide range of ecological and demographic conditions. This study attempts to correlate the extent of genetic diversity in MHC loci with parasite prevalence in free-living, natural populations of rainforest birds that vary in population size and degree of geographic isolation.

For example, our team is studying how ecological factors, and anthropogenic changes in habitat structure and connectivity affect the incidence and prevalence of avian malaria. Our study design takes advantage of a series of natural habitats that vary in size and isolation as well as species composition. Specifically, we are studying malaria in rainforest passerine bird species that live in a range of habitats from pristine rainforest to highly isolated and disturbed secondary plantation forests. We predict the malaria incidence will be a function of habitat structure, human disturbance levels and isolation. Identification of ecological variables critical to the persistence and prevalence of malaria will be fundamental to predicting the presence of malaria and emerging disease. Passerines have long been a model for human malaria, and because birds are habitat specific, their study is more likely to illuminate the habitat associated causes of malaria than study of high mobile and disease protected humans. Remote sensing data will be used to study the changes in the habitats over the years that the bird samples were collected. The combination of these data will lead to the development of predictive models on the spatial distribution of disease, and how habitat alteration may affect this distribution. Finally, the results will also assist the development of predictive models of disease transmission that result from habitat changes caused by global climate change.




Last modified July 10, 2002